WO2002061144A2 - Diagnostic de tumeur cerebrale et prediction de resultat de traitement - Google Patents

Diagnostic de tumeur cerebrale et prediction de resultat de traitement Download PDF

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Publication number
WO2002061144A2
WO2002061144A2 PCT/US2002/003160 US0203160W WO02061144A2 WO 2002061144 A2 WO2002061144 A2 WO 2002061144A2 US 0203160 W US0203160 W US 0203160W WO 02061144 A2 WO02061144 A2 WO 02061144A2
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gene expression
genes
gene
sample
class
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PCT/US2002/003160
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English (en)
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WO2002061144A8 (fr
WO2002061144A3 (fr
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Todd R. Golub
Eric S. Lander
Scott Pomeroy
Pablo Tamayo
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Whitehead Institute For Biomedical Research
Dana-Farber Cancer Institute, Inc.
Children's Medical Center Corporation
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Priority to EP20020704342 priority Critical patent/EP1356114A2/fr
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Publication of WO2002061144A8 publication Critical patent/WO2002061144A8/fr
Publication of WO2002061144A3 publication Critical patent/WO2002061144A3/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57407—Specifically defined cancers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • G16B25/10—Gene or protein expression profiling; Expression-ratio estimation or normalisation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/20—Supervised data analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/30—Unsupervised data analysis
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/112—Disease subtyping, staging or classification
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding

Definitions

  • Embryonal tumors of the central nervous system represent a heterogeneous group of tumors about which little is known biologically, and whose diagnosis, based on morphologic appearance alone, is controversial.
  • brain tumors can be classified using molecular distinctions that discriminate between, for example, medulloblastomas and other brain tumors.
  • Molecular distinctions can also be made, for example, for including primitive neuroectodemial tumors (hereinafter, "PNET”), atypical teratoid/rhabdoid tumors (AT/RT) and malignant gliomas.
  • PNET primitive neuroectodemial tumors
  • AT/RT atypical teratoid/rhabdoid tumors
  • malignant gliomas malignant gliomas.
  • the present invention is directed to a method for evaluating candidate therapeutic agents (e.g., drugs) for their effectiveness in treating brain tumors comprising: obtaining a sample of cells derived from a brain tumor; isolating a gene expression product from at least one informative gene from one or more cells in said sample; and determining a gene expression profile of at least one informative gene, such that the gene expression profile is correlated with the effectiveness of the drug candidate in treating brain tumors.
  • candidate therapeutic agents e.g., drugs
  • the present invention is directed to a method for monitoring the efficacy of a brain tumor treatment comprising: obtaining samples of cells at various time points derived from a patient being treated; determining the expression profile of the samples; classifying the samples for treatment outcome based on the expression profile; and comparing the treatment outcome class of the samples at various times during treatment, such that the efficacy of brain tumor treatment is determined.
  • Figures 3A-3B show a list of informative genes whose expression is low in meduUoblastoma and high in ghoblastoma.
  • the genes are identified by GenBank
  • a gene expression profile can comprise data for one or more genes and can be measured at a single time point or over a period of time.
  • Phenotype classification e.g., treatment outcome, brain tumor type
  • Phenotype classification can be made by comparing the gene expression profile of the sample to one or more gene expression profiles (e.g., in a database). Specific classifications involve comparing common informative genes whose expression is included in both expression profiles. Informative genes include, but are not limited to, those shown in Figures 1A and IB, 2A-2B; 3A-3B, 5A-5B and 6B-6C.
  • the gene expression product is mRNA and the gene expression levels are obtained, e.g., by contacting the sample with a suitable microarray on which probes specific for all or a subset of the informative genes have been immobilized, and determining the extent of hybridization of the nucleic acid in the sample to the probes on the microarray.
  • a suitable microarray on which probes specific for all or a subset of the informative genes have been immobilized, and determining the extent of hybridization of the nucleic acid in the sample to the probes on the microarray.
  • Such microarrays are also within the scope of the invention. Examples of methods of making oligonucleotide microarrays are described, for example, in WO 95/11995. Other methods are readily known to the skilled artisan.
  • the gene expression value measured or assessed is the numeric value obtained from an apparatus that can measure gene expression levels.
  • Gene expression levels refer to the amount of expression of the gene expression product, as described herein.
  • the values are raw values from the apparatus, or values that are optionally re-scaled, filtered and/or normalized. Such data is obtained, for example, from a GeneChip® probe array or Microarray (Affymetrix, Inc.; U.S. Patent Nos.
  • the nucleic acid to be analyzed (e.g., the target) is isolated, amplified and labeled with a detectable label, (e.g., 32 P or fluorescent label) prior to hybridization to the arrays.
  • a detectable label e.g. 32 P or fluorescent label
  • the arrays are inserted into a scanner that can detect patterns of hybridization. These patterns are detected by detecting the labeled target now attached to the microarray, e.g., if the target is fluorescently labeled, the hybridization data are collected as light emitted from the labeled groups.
  • V g a g (x g - b g ),
  • the present invention can be applied to screen potential drug candidates for their efficacy in treating brain tumors, i this embodiment, a sample's expression profile is compared before and after treatment with the candidate drug, wherein a shift in the gene expression profile in the treated sample from a profile correlated with poor treatment outcome to a profile correlated with improved treatment outcome is evidence for the efficacy of the drug in treating brain tumors.
  • a clinical challenge concerning meduUoblastoma is the highly variable response of patients to therapy. Whereas some patients are cured by chemotherapy and radiation, others have progressive disease. Cunently, the only prognostic factor used in clinical practice is tumor staging, a reflection of postoperative tumor size and the presence of metastases. Unfortunately, staging-based prognostication is imperfect in that many patients with low stage disease still succumb to their disease. There are cunently no molecular markers of outcome used in clinical practice for any brain tumor. High levels of expression of the neurofropl ⁇ in-3 receptor (TrkC), however, have been reported to conelate with a favorable meduUoblastoma outcome, suggesting a molecular basis of meduUoblastoma outcome variability (Segal, R.
  • TrkC neurofropl ⁇ in-3 receptor
  • Fig. 6B and 6C A number of genes not previously associated with clinical outcome were identified (Fig. 6B and 6C). Those conelated with favorable outcome included many genes characteristic of cerebellar differentiation (vesicle coat protein beta-NAP, NSCL-1, TrkC, sodium channels), and genes encoding extracellular matrix proteins (PLOD lysyl hydroxylase, collagen type Via, elastin). As expected, TrkC expression was conelated with a favorable outcome, consistent with prior reports of this association (Segal, R. et al, 1994. Proc. Natl. Acad. Sci. USA, 91:12867-12871; Kim, J. et al, 1999. Cancer Res., 59:711-719; Grotzer, M. et al, 2000.

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Abstract

La présente invention concerne des techniques de prédiction de classes phénotypiques des tumeurs cérébrales, telles qu'un type de tumeur cérébrale ou qu'un résultat de traitement, destinées à des prélèvements de tumeur cérébrale fondés sur des profils d'expression génique.
PCT/US2002/003160 2001-01-31 2002-01-31 Diagnostic de tumeur cerebrale et prediction de resultat de traitement WO2002061144A2 (fr)

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1592811A2 (fr) * 2003-02-11 2005-11-09 Wyeth Procedes pour controler in vivo des activites de medicaments
EP1608776A2 (fr) * 2003-04-03 2005-12-28 Wyeth Methodes de surveillance d'activites de medicaments in vivo
EP1669451A1 (fr) * 2003-09-01 2006-06-14 Japan Science and Technology Agency Marqueur de tumeur cerebrale et procede pour diagnostiquer une tumeur cerebrale
WO2006089185A2 (fr) * 2005-02-18 2006-08-24 Wyeth Marqueurs pharmacogenomiques pour le pronostic de tumeurs solides
WO2007012937A3 (fr) * 2005-07-26 2007-05-18 Council Scient Ind Res Methode de diagnostic du gliome avec distinction entre types progressif et de novo
US8321137B2 (en) 2003-09-29 2012-11-27 Pathwork Diagnostics, Inc. Knowledge-based storage of diagnostic models
US8977506B2 (en) 2003-09-29 2015-03-10 Response Genetics, Inc. Systems and methods for detecting biological features

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US20040010481A1 (en) * 2001-12-07 2004-01-15 Whitehead Institute For Biomedical Research Time-dependent outcome prediction using neural networks
US20050069863A1 (en) * 2003-09-29 2005-03-31 Jorge Moraleda Systems and methods for analyzing gene expression data for clinical diagnostics
US20070154889A1 (en) * 2004-06-25 2007-07-05 Veridex, Llc Methods and reagents for the detection of melanoma
US20080307537A1 (en) * 2005-03-31 2008-12-11 Dana-Farber Cancer Institute, Inc. Compositions and Methods for the Identification, Assessment, Prevention, and Therapy of Neurological Diseases, Disorders and Conditions
US7799519B2 (en) * 2005-07-07 2010-09-21 Vanderbilt University Diagnosing and grading gliomas using a proteomics approach
DE102005056365A1 (de) * 2005-11-25 2007-05-31 Vogt, Ulf, Dr. rer. nat. Verfahren zur individualisierten Prognose, Therapieempfehlung und/oder -verfolgung und/oder Nachsorge einer Tumorerkrankung
ES2763537T3 (es) * 2008-09-16 2020-05-29 Beckman Coulter Inc Diagrama de árbol interactivo para datos de citometría de flujo
US20150119267A1 (en) * 2012-04-16 2015-04-30 Sloan-Kettering Institute For Cancer Research Inhibition of colony stimulating factor-1 receptor signaling for the treatment of brain cancer
CN106191215B (zh) * 2015-04-29 2020-03-24 中国科学院上海生命科学研究院 肌肉萎缩相关的蛋白质分子标记Dkk-3的筛选及其应用

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Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1592811A2 (fr) * 2003-02-11 2005-11-09 Wyeth Procedes pour controler in vivo des activites de medicaments
EP1608776A2 (fr) * 2003-04-03 2005-12-28 Wyeth Methodes de surveillance d'activites de medicaments in vivo
EP1669451A1 (fr) * 2003-09-01 2006-06-14 Japan Science and Technology Agency Marqueur de tumeur cerebrale et procede pour diagnostiquer une tumeur cerebrale
EP1669451A4 (fr) * 2003-09-01 2007-02-14 Japan Science & Tech Agency Marqueur de tumeur cerebrale et procede pour diagnostiquer une tumeur cerebrale
US8321137B2 (en) 2003-09-29 2012-11-27 Pathwork Diagnostics, Inc. Knowledge-based storage of diagnostic models
US8977506B2 (en) 2003-09-29 2015-03-10 Response Genetics, Inc. Systems and methods for detecting biological features
WO2006089185A2 (fr) * 2005-02-18 2006-08-24 Wyeth Marqueurs pharmacogenomiques pour le pronostic de tumeurs solides
WO2006089185A3 (fr) * 2005-02-18 2006-09-28 Wyeth Corp Marqueurs pharmacogenomiques pour le pronostic de tumeurs solides
WO2007012937A3 (fr) * 2005-07-26 2007-05-18 Council Scient Ind Res Methode de diagnostic du gliome avec distinction entre types progressif et de novo

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US20020155480A1 (en) 2002-10-24
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